(Informative)
Technical Specification: AI Framework (MPAI-AIF) V2.1 is a key element of the MPAI approach to AI-based Data Coding standards. It is based on a framework enabling initialisation, dynamic configuration, and control of AIWs in the standard AI Framework environment depicted in Figure 1. The Data Data produced by executing specific functions by AI Modules (AIM) are communicate to other AIMs in the AIW.
The effectiveness of the functions perform may the AIMs may be improved if they know more about the capabilities of the AIMs they are connected to and the Data they receive. For instance, an instance of the MPAI Natural Language Processing (MMC-NLU) AIM has the task to refine the text received and produce its Meaning using three levels of information:
- Just the input text.
- The object identifiers referenced in the text.
- The object context in a relevant space.
The cases correspond with different levels of AIM capabilities that likely correspond to improved accuracy of the refined text and Meaning produced when moving from the first to the third case.
Technical Specification: AI Module Profiles (MPAI-PRF) enables an AIM instance to signal its Attributes – such as input data, output data, and functionality – and Sub-Attributes – such as languages supported by a Text and Speech Translation AIM – that uniquely characterise the AIM. Currently, MPAI-PRF defines the Attributes of eight AIMs but Profiles for more AIMs are likely to be defined in the future.
The effectiveness of the functions performed by an AIM can also be enabled or enhanced if the AIM knows more about the characteristics of the Data received. Examples of characteristics include:
- The CIE 1931 colour space of an instance of the Visual Data Type.
- The MP3 format of a speech segment.
- The WAV file format of an audio segment.
- The gamma correction applied to the device that produced a video.
- The Instance ID of an object in an audio segment.
- The Text conveyed by a speech segment.
Technical Specification: Data Types, Formats, and Attributes (MPAI-TFA) V1.2 specifies the Qualifier Data Type, a container that can be used to represent, for instance, that a Visual Data Type instance:
- Uses a given colour space (Sub-Type)
- Was produced by an AVC codec (Format).
- Is described by Dublin Core Metadata (Attribute).
Therefore, Qualifiers are a specialised type of metadata intended to support the operation of AIMs receiving data from other AIMs and conveying information on Sub-Types, Formats, and Attributes related to the Content. Qualifiers are intended to convey information for use by an AIM. They are human-readable but intended only to be used by AIMs. The combination of “Content” (the Data of a Data Type) and “Qualifier” (the combination of Sub-Type, Format, and Attributes) is called “Object”.
MPAI provides a standard method to attach information to a Data Type instance called Annotation defined as Data attached to an Object or a Scene. As opposed to Qualifier that describes intrinsic properties of a Data Type, an Annotation is spatially and temporally local and changeable.
MPAI plans of publishing new versions of MPAI-TFA because of the large variety of applications requiring Qualifiers and the need for extending existing Qualifiers. MPAI-TFA users may communicate their need for extension of existing and specification of additional Data Type Qualifiers to the MPAI Secretariat. Therefore, versioning of Qualifiers is a critical component of MPAI-TFA.
The Chapters, Sections, and Annexes of this Technical Specification are Normative unless they are explicitly labelled as Informative. In all Chapters and Sections, Terms beginning with a capital letter are defined in Table 1 if they are specific to this Technical Specification and in Table 2 if they are common to all MPAI Technical Specifications. All Chapters and Annexes are Normative unless they are labelled as Informative.
